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Machines, Volume 9, Issue 10 (October 2021) – 40 articles

Cover Story (view full-size image): Early-stage fatigue damage detection in metal components is critical to ensure reliability and facilitate predictive maintenance. This article uses novel experiments and introduces a combined pattern recognition and machine learning approach to detect fatigue cracks at the micron-scale. In summary, the article opens future opportunities for designing a robust predictive maintenance framework. View this paper
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Review
A Systematic Review of Product Design for Space Instrument Innovation, Reliability, and Manufacturing
Machines 2021, 9(10), 244; https://doi.org/10.3390/machines9100244 - 19 Oct 2021
Viewed by 364
Abstract
The design and development of space instruments are considered to be distinct from that of other products. It is because the key considerations are vastly different from those that govern the use of products on planet earth. The service life of a space [...] Read more.
The design and development of space instruments are considered to be distinct from that of other products. It is because the key considerations are vastly different from those that govern the use of products on planet earth. The service life of a space instrument, its use in extreme space environments, size, weight, cost, and the complexity of maintenance must all be considered. As a result, more innovative ideas and resource support are required to assist mankind in space exploration. This article reviews the impact of product design and innovation on the development of space instruments. Using a systematic literature search review and classification, we have identified over 129 papers and finally selected 48 major articles dealing with space instrument product innovation design. According to the studies, it is revealed that product design and functional performance is the main research focuses on the studied articles. The studies also highlighted various factors that affect space instrument manufacturing or fabrication, and that innovativeness is also the key in the design of space instruments. Lastly, the product design is important to affect the reliability of the space instrument. This review study provides important information and key considerations for the development of smart manufacturing technologies for space instruments in the future. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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Article
Verification of a Body Freedom Flutter Numerical Simulation Method Based on Main Influence Parameters
Machines 2021, 9(10), 243; https://doi.org/10.3390/machines9100243 - 18 Oct 2021
Viewed by 289
Abstract
The body freedom flutter characteristics of an airfoil and a fly wing aircraft model were calculated based on a CFD method for the Navier–Stokes equations. Firstly, a rigid elastic coupling dynamic model of a two-dimensional airfoil with a free–free boundary condition was derived [...] Read more.
The body freedom flutter characteristics of an airfoil and a fly wing aircraft model were calculated based on a CFD method for the Navier–Stokes equations. Firstly, a rigid elastic coupling dynamic model of a two-dimensional airfoil with a free–free boundary condition was derived in an inertial frame and decoupled by rigid body mode and elastic mode. In the fluid–solid coupling method, the rigid body was trimmed by subtracting the generalized steady aerodynamic force from the structural dynamic equation. The flutter characteristics were predicted by the variable stiffness method at a fixed Mach number and flight altitude. Finally, validation of the predicted body freedom flutter characteristics was performed through a comparison of theoretical solutions based on a Theodorsen unsteady aerodynamic model for airfoil and experimental results for a fly wing aircraft model. The mechanism of the influence of the bending mode stiffness and the position of the center of gravity on the body freedom flutter characteristics were briefly analyzed. Full article
(This article belongs to the Special Issue Dynamic Stability Analysis of Aerospace Structures)
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Article
Research on Drilling Rate Optimization of a UCS Identification System While Drilling for Coal Mine Roadway Roofs
Machines 2021, 9(10), 242; https://doi.org/10.3390/machines9100242 - 18 Oct 2021
Viewed by 274
Abstract
In this paper, to identify the roof unconfined compressive strength (UCS) in the process of coal mine roadway support in real-time and optimize the real-time drilling speed while drilling, this paper proposes and establishes a drilling test method for assessing the uniaxial compressive [...] Read more.
In this paper, to identify the roof unconfined compressive strength (UCS) in the process of coal mine roadway support in real-time and optimize the real-time drilling speed while drilling, this paper proposes and establishes a drilling test method for assessing the uniaxial compressive strength (UCS) of a roof. This method can be used to optimize the speed of drilling. Moreover, a mathematical model of the power output is developed for a roof-strata identification system with a drilling test system. The results were as follows: (1) the system was able to identify the uniaxial compressive strength of roof rock; (2) the pressure of the drill leg of the pneumatic bolt did not match the output power of the pneumatic motor, the pneumatic motor could not reach the maximum power point, and the insufficient thrust of the pneumatic leg led to failure of the maximum output power of the pneumatic motor; (3) to increase the output power of the air motor and thus improve the drilling speed, we applied a booster valve for the system. The experimental results show that the power of the air motor has a linear relationship with drilling speed. In this way, the speed of the drill can be increased by increasing the motor power. Full article
(This article belongs to the Special Issue Dynamics and Diagnostics of Heavy-Duty Industrial Machines)
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Article
Fast Attitude Estimation System for Unmanned Ground Vehicle Based on Vision/Inertial Fusion
Machines 2021, 9(10), 241; https://doi.org/10.3390/machines9100241 - 18 Oct 2021
Viewed by 307
Abstract
The attitude estimation system based on vision/inertial fusion is of vital importance and great urgency for unmanned ground vehicles (UGVs) in GNSS-challenged/denied environments. This paper aims to develop a fast vision/inertial fusion system to estimate attitude; which can provide attitude estimation for UGVs [...] Read more.
The attitude estimation system based on vision/inertial fusion is of vital importance and great urgency for unmanned ground vehicles (UGVs) in GNSS-challenged/denied environments. This paper aims to develop a fast vision/inertial fusion system to estimate attitude; which can provide attitude estimation for UGVs during long endurance. The core idea in this paper is to integrate the attitude estimated by continuous vision with the inertial pre-integration results based on optimization. Considering that the time-consuming nature of the classical methods comes from the optimization and maintenance of 3D feature points in the back-end optimization thread, the continuous vision section calculates the attitude by image matching without reconstructing the environment. To tackle the cumulative error of the continuous vision and inertial pre-integration, the prior attitude information is introduced for correction, which is measured and labeled by an off-line fusion of multi-sensors. Experiments with the open-source datasets and in road environments have been carried out, and the results show that the average attitude errors are 1.11° and 1.96°, respectively. The road test results demonstrate that the processing time per frame is 24 ms, which shows that the proposed system improves the computational efficiency. Full article
(This article belongs to the Special Issue Nonlinear and Optimal, Real-Time Control of UAV)
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Article
Research on Adaptive Control of Air-Borne Bolting Rigs Based on Genetic Algorithm Optimization
Machines 2021, 9(10), 240; https://doi.org/10.3390/machines9100240 - 18 Oct 2021
Viewed by 325
Abstract
Rotation speed and propulsive force are the two critical parameters in the work of the air-borne bolting rig. To address the problem that unreasonable rotation speed and propulsive force will induce the breakage of the drill pipe and the inability of the drill [...] Read more.
Rotation speed and propulsive force are the two critical parameters in the work of the air-borne bolting rig. To address the problem that unreasonable rotation speed and propulsive force will induce the breakage of the drill pipe and the inability of the drill bit to cut coal adequately this paper proposes an adaptive control strategy for the air-borne bolting rig based on genetic algorithm optimization. Firstly, we obtain the corresponding coal hardness by the real-time acquisition of the working torque of the drill pipe. Then we calculate the reasonable rotation speed of the hydraulic motor and the propulsive force of the hydraulic cylinder on the coal of different hardness. Secondly, the genetic algorithm is applied to optimize the parameters of the PID (proportion integration differentiation) controller so that the system may attain the target value fast and reliably and achieve adaptive control. Finally, a simulation model of the slewing system and the propulsion system of the air-borne bolting rig are established in the AMESim hydraulic software, and the simulation tests were carried out under two distinct working conditions: single coal hardness and coal hardness of sudden change. The results indicate that the PID control strategy based on genetic algorithm optimization has a shorter response time, a smaller overshoot, and a lower steady-state error than the traditional PID control strategy. Full article
(This article belongs to the Special Issue Dynamics and Diagnostics of Heavy-Duty Industrial Machines)
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Article
A 1D–3D Approach for Fast Numerical Analysis of the Flow Characteristics of a Diesel Engine Exhaust Gas
Machines 2021, 9(10), 239; https://doi.org/10.3390/machines9100239 - 17 Oct 2021
Viewed by 395
Abstract
It is necessary to analyze the intake/exhaust gas flow of a diesel engine when turbocharger matching and when installing emission control devices such as exhaust gas recirculation (EGR), selective catalytic reduction (SCR), and scrubbers. Analyzing the intake/exhaust gas flow using a 3D approach [...] Read more.
It is necessary to analyze the intake/exhaust gas flow of a diesel engine when turbocharger matching and when installing emission control devices such as exhaust gas recirculation (EGR), selective catalytic reduction (SCR), and scrubbers. Analyzing the intake/exhaust gas flow using a 3D approach can use various analytical models, but it requires a significant amount of time to perform the computation. An approach that combines 1D and 3D is a fast numerical analysis method that can utilize the analysis models of the 3D approach and obtain accurate calculation results. In this study, the flow characteristics of the exhaust gas were analyzed using a 1D–3D coupling algorithm to analyze the unsteady gas flow of a diesel engine, and whether the 1D–3D approach was suitable for analyzing exhaust systems was evaluated. The accuracy of the numerical analysis results was verified by comparison with the experimental results, and the flow characteristics of various shapes of the exhaust system of a diesel engine could be analyzed. Numerical analysis using the 1D–3D approach was able to be computed about 300 times faster than the 3D approach, and it was a method that could be used for research focused on the exhaust system. In addition, since it could quickly and accurately calculate intake/exhaust gas flow, it was expected to be used as a numerical analysis method suitable for analyzing the interaction of diesel engines with emission control devices and turbochargers. Full article
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Article
Bearing Remaining Useful Life Prediction Based on a Scaled Health Indicator and a LSTM Model with Attention Mechanism
Machines 2021, 9(10), 238; https://doi.org/10.3390/machines9100238 - 16 Oct 2021
Viewed by 485
Abstract
Rotor systems are of considerable importance in most modern industrial machinery, and the evaluation of the working conditions and longevity of their core component—the rolling bearing—has gained considerable research interest. In this study, a scale-normalized bearing health indicator based on the improved phase [...] Read more.
Rotor systems are of considerable importance in most modern industrial machinery, and the evaluation of the working conditions and longevity of their core component—the rolling bearing—has gained considerable research interest. In this study, a scale-normalized bearing health indicator based on the improved phase space warping (PSW) and hidden Markov model regression was established. This indicator was then used as the input for the encoder–decoder LSTM neural network with an attention mechanism to predict the rolling bearing RUL. Experiments show that compared with traditional health indicators such as kurtosis and root mean square (RMS), this scale-normalized bearing health indicator directly indicates the actual damage degree of the bearing, thereby enabling the LSTM model to predict RUL of the bearing more accurately. Full article
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Article
Kinematic Analysis and Parameter Measurement for Multi-Axis Laser Engraving Machine Tools
Machines 2021, 9(10), 237; https://doi.org/10.3390/machines9100237 - 16 Oct 2021
Viewed by 352
Abstract
Multi-axis Laser Engraving Machine Tools (LEMT) are widely used in precision processing of parts with complex surface. The accuracy of kinematic model and parameter measurement are the key factors determining the processing quality of LEMT. In this paper, a kinematic model of multi-axis [...] Read more.
Multi-axis Laser Engraving Machine Tools (LEMT) are widely used in precision processing of parts with complex surface. The accuracy of kinematic model and parameter measurement are the key factors determining the processing quality of LEMT. In this paper, a kinematic model of multi-axis LEMT was established based on Homogeneous Transformation Matrix (HTM). Two types of unknown parameters, linkage parameters and positioning parameters, were measured in the presented model. Taking advantage of the characteristics of laser processing, this paper proposed a rapid measurement method of linkage parameters by combining the machine tool motion with the laser marking action. For positioning parameters, this study proposed a non-contact measurement method based on structured light scanner, which can obtain the translation values and the rotation values from the Workpiece Coordinate System (WCS) to the Basic Coordinate System (BCS) simultaneously. After the measurement of two kinds of parameters of a multi-axis LEMT was completed, the processing of a spatial curve was performed and the average contour error was controlled at 15.1 μm, which is sufficient to meet the project requirements. Full article
(This article belongs to the Special Issue Robotic Machine Tools)
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Article
Intelligent Control of Swarm Robotics Employing Biomimetic Deep Learning
Machines 2021, 9(10), 236; https://doi.org/10.3390/machines9100236 - 14 Oct 2021
Viewed by 354
Abstract
The collective motion of biological species has robust and flexible characteristics. Since the individual of the biological group interacts with other neighbors asymmetrically, which means the pairwise interaction presents asymmetrical characteristics during the collective motion, building the model of the pairwise interaction of [...] Read more.
The collective motion of biological species has robust and flexible characteristics. Since the individual of the biological group interacts with other neighbors asymmetrically, which means the pairwise interaction presents asymmetrical characteristics during the collective motion, building the model of the pairwise interaction of the individual is still full of challenges. Based on deep learning (DL) technology, experimental data of the collective motion on Hemigrammus rhodostomus fish are analyzed to build an individual interaction model with multi-parameter input. First, a Deep Neural Network (DNN) structure for pairwise interaction is designed. Then, the interaction model is obtained by means of DNN proper training. We propose a novel key neighbor selection strategy, which is called the Largest Visual Pressure Selection (LVPS) method, to deal with multi-neighbor interaction. Based on the information of the key neighbor identified by LVPS, the individual uses the properly trained DNN model for the pairwise interaction. Compared with other key neighbor selection strategies, the statistical properties of the collective motion simulated by our proposed DNN model are more consistent with those of fish experiments. The simulation shows that our proposed method can extend to large-scale group collective motion for aggregation control. Thereby, the individual can take advantage of quite limited local information to collaboratively achieve large-scale collective motion. Finally, we demonstrate swarm robotics collective motion in an experimental platform. The proposed control method is simple to use, applicable for different scales, and fast for calculation. Thus, it has broad application prospects in the fields of multi-robotics control, intelligent transportation systems, saturated cluster attacks, and multi-agent logistics, among other fields. Full article
(This article belongs to the Section Automation Systems)
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Article
Key-Phase-Free Blade Tip-Timing for Nonstationary Test Conditions: An Improved Algorithm for the Vibration Monitoring of a SAFRAN Turbomachine from the Surveillance 9 International Conference Contest
Machines 2021, 9(10), 235; https://doi.org/10.3390/machines9100235 - 13 Oct 2021
Viewed by 323
Abstract
A turbomachine is a fundamental engineering apparatus meant to transfer energy between a rotor and a fluid. Turbomachines are the core of power generation in many engineering applications such as electric power generation plants, aerospace, marine power, automotive etc. Their relevance makes them [...] Read more.
A turbomachine is a fundamental engineering apparatus meant to transfer energy between a rotor and a fluid. Turbomachines are the core of power generation in many engineering applications such as electric power generation plants, aerospace, marine power, automotive etc. Their relevance makes them both mission critical and safety critical in many fields. To foster reliability and safety, then, continuous monitoring of the rotor is more than desirable. One promising monitoring technique is, with no doubt, the Blade Tip-Timing, which, being simple and non-invasive, can be easily implemented on many different rotors. Blade Tip-Timing is based on the recording of the time of arrival of the blades passing in front of a probe located at a fixed angular position. The non-contact nature of the measurement prevents influences on the measured vibration, that can be recovered for all the blades simultaneously, possibly even online. In this regard, a novel algorithm is presented in this paper for obtaining a good estimate of the vibration of the blades with minimum system complexity (i.e., only one Blade Tip-Timing probe) and minimum computational effort, so to create a simple vibration monitoring system, potentially implementable online. The methodology was tested on a dataset from a SAFRAN turbomachine made available during the Surveillance 9 international conference for a diagnostic contest. Full article
(This article belongs to the Special Issue Feature Papers to Celebrate the First Impact Factor of Machines)
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Article
Challenges in Winding Design and Thermal Calculations: Physical Model of Permanent Magnet Synchronous Machine
Machines 2021, 9(10), 234; https://doi.org/10.3390/machines9100234 - 13 Oct 2021
Viewed by 288
Abstract
Interest in multilayer windings is increasing with the application of the hairpin winding technology to the manufacturing of electrical machines. Therefore, the four-layer fractional slot concentrated winding is used for the initial design of the machine in this paper. The proposed physical model [...] Read more.
Interest in multilayer windings is increasing with the application of the hairpin winding technology to the manufacturing of electrical machines. Therefore, the four-layer fractional slot concentrated winding is used for the initial design of the machine in this paper. The proposed physical model of the machine uses winding with a relatively high number of turns which is inappropriate to hairpin winding. Therefore the round-wire winding is created and the three-layer winding is derived and analyzed including the effect on the slot leakage inductance. The thermal analysis is then applied to the physical model of the machine to evaluate the slot-related thermal properties of the slot and the whole machine. The measurement is compared with the finite element analysis (FEA) and the equivalent slot thermal conductivity and heat transfer coefficients of the stator and rotor are obtained. Full article
(This article belongs to the Special Issue Thermal Analysis of Electric Machine Drives)
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Article
Grape Berry Detection and Size Measurement Based on Edge Image Processing and Geometric Morphology
Machines 2021, 9(10), 233; https://doi.org/10.3390/machines9100233 - 13 Oct 2021
Cited by 1 | Viewed by 494
Abstract
Counting grape berries and measuring their size can provide accurate data for robot picking behavior decision-making, yield estimation, and quality evaluation. When grapes are picked, there is a strong uncertainty in the external environment and the shape of the grapes. Counting grape berries [...] Read more.
Counting grape berries and measuring their size can provide accurate data for robot picking behavior decision-making, yield estimation, and quality evaluation. When grapes are picked, there is a strong uncertainty in the external environment and the shape of the grapes. Counting grape berries and measuring berry size are challenging tasks. Computer vision has made a huge breakthrough in this field. Although the detection method of grape berries based on 3D point cloud information relies on scanning equipment to estimate the number and yield of grape berries, the detection method is difficult to generalize. Grape berry detection based on 2D images is an effective method to solve this problem. However, it is difficult for traditional algorithms to accurately measure the berry size and other parameters, and there is still the problem of the low robustness of berry counting. In response to the above problems, we propose a grape berry detection method based on edge image processing and geometric morphology. The edge contour search and the corner detection algorithm are introduced to detect the concave point position of the berry edge contour extracted by the Canny algorithm to obtain the best contour segment. To correctly obtain the edge contour information of each berry and reduce the error grouping of contour segments, this paper proposes an algorithm for combining contour segments based on clustering search strategy and rotation direction determination, which realizes the correct reorganization of the segmented contour segments, to achieve an accurate calculation of the number of berries and an accurate measurement of their size. The experimental results prove that our proposed method has an average accuracy of 87.76% for the detection of the concave points of the edge contours of different types of grapes, which can achieve a good edge contour segmentation. The average accuracy of the detection of the number of grapes berries in this paper is 91.42%, which is 4.75% higher than that of the Hough transform. The average error between the measured berry size and the actual berry size is 2.30 mm, and the maximum error is 5.62 mm, which is within a reasonable range. The results prove that the method proposed in this paper is robust enough to detect different types of grape berries. Full article
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Article
A GEMMA-GRAFCET Generator for the Automation Software of Smart Manufacturing Systems
Machines 2021, 9(10), 232; https://doi.org/10.3390/machines9100232 - 12 Oct 2021
Viewed by 358
Abstract
Within the Industry 4.0 revolution, manufacturing enterprises are transforming to intelligent enterprises constituted by Smart Manufacturing Systems (SMSs). A key capability of SMSs is the ability to connect and communicate with each other through Industrial Internet of Things technologies, and protocols with standard [...] Read more.
Within the Industry 4.0 revolution, manufacturing enterprises are transforming to intelligent enterprises constituted by Smart Manufacturing Systems (SMSs). A key capability of SMSs is the ability to connect and communicate with each other through Industrial Internet of Things technologies, and protocols with standard syntax and semantics. In this context, the GEMMA-GRAFCET Methodology (GG-Methodology) provides a standard approach and vocabulary for the management of the Operational Modes (OMs) of SMSs through the automation software, bringing a common understanding of the exchanged data. Considering the lack of tools to implement the methodology, this work introduces an online tool based on Model-Driven Engineering–GEMMA-GRAFCET Generator (GG-Generator)–to specify and generate PLCopen XML code compliant with the GG-Methodology. The proposed GG-Generator is applied to a case study and validated using Virtual Commissioning and Dynamic Software Testing. Due to the consistency obtained between the GG-Methodology and the generated PLC code, the GG-Generator is expected to support the adoption of the methodology, thus contributing to the interoperability of SMSs through the standardization of the automation software for the management of their OMs. Full article
(This article belongs to the Special Issue Intelligent Machines and Control Systems)
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Article
A Digital Twin-Oriented Lightweight Approach for 3D Assemblies
Machines 2021, 9(10), 231; https://doi.org/10.3390/machines9100231 - 09 Oct 2021
Viewed by 576
Abstract
In the design and operation scenarios driven by Digital Twins, large computer-aided design (CAD) models of production line equipment can limit the real-time performance and fidelity of the interaction between digital and physical entities. Digital CAD models often consist of combined parts with [...] Read more.
In the design and operation scenarios driven by Digital Twins, large computer-aided design (CAD) models of production line equipment can limit the real-time performance and fidelity of the interaction between digital and physical entities. Digital CAD models often consist of combined parts with characteristics of discrete folded corner planes. CAD models simplified to a lower resolution by current mainstream mesh simplification algorithms might suffer from significant feature loss and mesh breakage, and the interfaces between the different parts cannot be well identified and simplified. A lightweight approach for common CAD assembly models of Digital Twins is proposed. Based on quadric error metrics, constraints of discrete folded corner plane characteristics of Digital Twin CAD models are added. The triangular regularity in the neighborhood of the contraction target vertices is used as the penalty function, and edge contraction is performed based on the cost. Finally, a segmentation algorithm is employed to identify and remove the interfaces between the two CAD assembly models. The proposed approach is verified through common stereoscopic warehouse, robot base, and shelf models. In addition, a scenario of a smart phone production line is applied. The experimental results indicate that the geometric error of the simplified mesh is reduced, the frame rate is improved, and the integrity of the geometric features and triangular facets is effectively preserved. Full article
(This article belongs to the Special Issue Digital Twin Applications in Smart Manufacturing)
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Article
A 3D Keypoints Voting Network for 6DoF Pose Estimation in Indoor Scene
Machines 2021, 9(10), 230; https://doi.org/10.3390/machines9100230 - 08 Oct 2021
Viewed by 364
Abstract
This paper addresses the problem of instance-level 6DoF pose estimation from a single RGBD image in an indoor scene. Many recent works have shown that a two-stage network, which first detects the keypoints and then regresses the keypoints for 6d pose estimation, achieves [...] Read more.
This paper addresses the problem of instance-level 6DoF pose estimation from a single RGBD image in an indoor scene. Many recent works have shown that a two-stage network, which first detects the keypoints and then regresses the keypoints for 6d pose estimation, achieves remarkable performance. However, the previous methods concern little about channel-wise attention and the keypoints are not selected by comprehensive use of RGBD information, which limits the performance of the network. To enhance RGB feature representation ability, a modular Split-Attention block that enables attention across feature-map groups is proposed. In addition, by combining the Oriented FAST and Rotated BRIEF (ORB) keypoints and the Farthest Point Sample (FPS) algorithm, a simple but effective keypoint selection method named ORB-FPS is presented to avoid the keypoints appear on the non-salient regions. The proposed algorithm is tested on the Linemod and the YCB-Video dataset, the experimental results demonstrate that our method outperforms the current approaches, achieves ADD(S) accuracy of 94.5% on the Linemod dataset and 91.4% on the YCB-Video dataset. Full article
(This article belongs to the Section Mechatronic and Intelligent Machines)
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Article
A Process Monitoring Method Based on Dynamic Autoregressive Latent Variable Model and Its Application in the Sintering Process of Ternary Cathode Materials
Machines 2021, 9(10), 229; https://doi.org/10.3390/machines9100229 - 07 Oct 2021
Cited by 1 | Viewed by 379
Abstract
Due to the ubiquitous dynamics of industrial processes, the variable time lag raises great challenge to the high-precision industrial process monitoring. To this end, a process monitoring method based on the dynamic autoregressive latent variable model is proposed in this paper. First, from [...] Read more.
Due to the ubiquitous dynamics of industrial processes, the variable time lag raises great challenge to the high-precision industrial process monitoring. To this end, a process monitoring method based on the dynamic autoregressive latent variable model is proposed in this paper. First, from the perspective of process data, a dynamic autoregressive latent variable model (DALM) with process variables as input and quality variables as output is constructed to adapt to the variable time lag characteristic. In addition, a fusion Bayesian filtering, smoothing and expectation maximization algorithm is used to identify model parameters. Then, the process monitoring method based on DALM is constructed, in which the process data are filtered online to obtain the latent space distribution of the current state, and T2 statistics are constructed. Finally, by comparing with an existing method, the feasibility and effectiveness of the proposed method is tested on the sintering process of ternary cathode materials. Detailed comparisons show the superiority of the proposed method. Full article
(This article belongs to the Special Issue Deep Learning-Based Machinery Fault Diagnostics)
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Article
Machinery Foundations Dynamical Analysis: A Case Study on Reciprocating Compressor Foundation
Machines 2021, 9(10), 228; https://doi.org/10.3390/machines9100228 - 07 Oct 2021
Viewed by 423
Abstract
A faulty dynamical interaction between a machine and a foundation can lead to unexpected and dangerous failures, impacting human lives and the environment. Some machines, as reciprocating compressors, have a low rotation speed; this can lead to dangerous frequency for the foundation blocks. [...] Read more.
A faulty dynamical interaction between a machine and a foundation can lead to unexpected and dangerous failures, impacting human lives and the environment. Some machines, as reciprocating compressors, have a low rotation speed; this can lead to dangerous frequency for the foundation blocks. For this reason, a careful analysis shall be done during the design phase to avoid the range of the frequency of resonances and low vibration speeds. Designers can approach this problem by relying both on Analytical Theory and Finite Element Analysis. This article compares these methods by studying the dynamical response of different foundation geometries in a case study of a reciprocating compressor foundation. The applicability limits of Analytical theory are explored and an evaluation of the difference in the estimation of natural frequencies of the system using Analytical Theory and Finite Elements Analysis are made for different foundation geometries. The comparison shows similar results until the foundation geometry is rigid; reference geometries limits are provided so that designers can choose which of the methods better suits their type of analysis. Full article
(This article belongs to the Section Machine Design and Theory)
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Article
Modular Segmented Motor for Power-Assist Wheelchairs: Proof of Concept
Machines 2021, 9(10), 227; https://doi.org/10.3390/machines9100227 - 06 Oct 2021
Viewed by 310
Abstract
This paper presents an analysis of the opportunity to increase the price availability of small electric vehicles, such as electric scooters, such as bicycles and wheelchairs, by applying expandability and modularity principles to their motors. Assuming that, in many cases, small electric vehicles [...] Read more.
This paper presents an analysis of the opportunity to increase the price availability of small electric vehicles, such as electric scooters, such as bicycles and wheelchairs, by applying expandability and modularity principles to their motors. Assuming that, in many cases, small electric vehicles are brought to the market in several power/price versions, the authors of this report evaluate the possibility of combining different numbers of electromechanical modules while, at the same time, maintaining the unity of the entire drive/motor scheme, thus making the mentioned expandability possible. Power-assist wheelchairs are taken as an example of the application, where such expandability is reasonable. The application provides a price reduction for the less powerful wheelchairs in the case of less severe disabilities. To start, the authors briefly compare multidrive schemes that ground the principle of modularity at the electromechanical level. Then, they outline a radially segmented motor concept and discuss this concept using the example of a permanent magnet synchronous motor. In particular, they propose a methodology for the calculation of its parameters and calculate the particular design details of such a motor. The motor is then analyzed with the help of its mathematical model, as well as experimentally. This tentative evaluation of two 50 W segments (of a 300 W 6-segment motor) proves that the proposed segmented modularity concept is feasible, and that it requires a more detailed consideration of the parameters and the other implementation aspects (power driver, control, cooling) of the given synchronous motor. Moreover, the concept might be successfully utilized in the designs of other motor types. Full article
(This article belongs to the Special Issue Design and Control of Electrical Machines)
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Article
Optimal Vibration Suppression Modification Method for High-Speed Helical Gear Transmission of Battery Electric Vehicles under Full Working Conditions
Machines 2021, 9(10), 226; https://doi.org/10.3390/machines9100226 - 03 Oct 2021
Viewed by 388
Abstract
To improve the working performance of battery electric vehicle (BEV) high-speed helical gear transmission under full working conditions, combined with Tooth Contact Analysis (TCA) and Loaded Tooth Contact Analysis (LTCA), the vibration model of single-stage helical gear bending-torsion-axis-swing coupling system considering time-varying mesh [...] Read more.
To improve the working performance of battery electric vehicle (BEV) high-speed helical gear transmission under full working conditions, combined with Tooth Contact Analysis (TCA) and Loaded Tooth Contact Analysis (LTCA), the vibration model of single-stage helical gear bending-torsion-axis-swing coupling system considering time-varying mesh stiffness was established. The genetic algorithm was used to optimize the tooth surface with the objective of minimizing the mean value of the vibration acceleration at full working conditions. Finally, a high-speed helical gear transmission system in a BEV gearbox was taken as a simulation example and the best-modified tooth surface at full working conditions was obtained. Experiment and simulation results show that the proposed calculation method of time-varying meshing stiffness is accurate, and tooth surface modification can effectively suppress the vibration of high-speed helical gear transmission in BEV; compared to the optimally modified tooth surface under a single load, the optimal modified tooth surface under full working conditions has a better vibration reduction effect over the entire working range. Full article
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Article
Numerical Optimization for the Impact Performance of a Rubber Ring Buffer of a Train Coupler
Machines 2021, 9(10), 225; https://doi.org/10.3390/machines9100225 - 02 Oct 2021
Viewed by 343
Abstract
Shock and vibration caused by mechanical motion bring huge potential threats to the service life and assembly reliability of mechanical systems. Rubber materials have been widely used in aircraft, trains, and other engineering fields, due to their excellent properties in shock and vibration [...] Read more.
Shock and vibration caused by mechanical motion bring huge potential threats to the service life and assembly reliability of mechanical systems. Rubber materials have been widely used in aircraft, trains, and other engineering fields, due to their excellent properties in shock and vibration absorption. This paper aimed to study the rubber ring buffer applied to a certain type of Chinese locomotive. Firstly, the finite element model was established and verified through experimental data. Based on the verified simulation model, the influence of the constitutive parameters (C01/C10 ratio height H and contour radius R) of the rubber ring on its energy absorption and peak crushing force under impact loading was studied in a numerical environment. Finally, the design of the experiment was carried out by the optimized Latin hypercube method, and the response surface model was established, which intuitively demonstrated the influence of the relevant parameters of the rubber ring on the change trend of the energy absorption and peak force. Based on the proxy model, the parameters that improve the crashworthiness of the rubber ring buffer were found quickly by the NSGA-II optimization algorithm, and the problems of a long calculation time and low optimization efficiency when using the conventional finite element method were avoided. The optimization results stated that when H = 107.57 mm and R = 85.70 mm, C01/C10 = 0.0571 of the energy absorption of the optimized buffer was increased by 59.03%, and the peak force was decreased by 14.37%, compared with the original structure. The optimized rubber ring buffer is expected to reduce the peak crushing force, enhance the energy absorption capacity, and mitigate the damage to the train system caused by shock and vibration. Full article
(This article belongs to the Section Material Processing Technology)
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Article
Design and Analysis of a Lower Limb Rehabilitation Training Component for Bedridden Stroke Patients
Machines 2021, 9(10), 224; https://doi.org/10.3390/machines9100224 - 30 Sep 2021
Viewed by 350
Abstract
Carrying out the immediate rehabilitation interventional therapy will better improve the curative effect of rehabilitation therapy, after the condition of bedridden stroke patients becomes stable. A new lower limb rehabilitation training module, as a component of a synchronous rehabilitation robot for bedridden stroke [...] Read more.
Carrying out the immediate rehabilitation interventional therapy will better improve the curative effect of rehabilitation therapy, after the condition of bedridden stroke patients becomes stable. A new lower limb rehabilitation training module, as a component of a synchronous rehabilitation robot for bedridden stroke patients’ upper and lower limbs, is proposed. It can electrically adjust the body shape of patients with a different weight and height. Firstly, the innovative mechanism design of the lower limb rehabilitation training module is studied. Then, the mechanism of the lower limb rehabilitation module is simplified and the geometric relationship of the human–machine linkage mechanism is deduced. Next, the trajectory planning and dynamic modeling of the human–machine linkage mechanism are carried out. Based on the analysis of the static moment safety protection of the human–machine linkage model, the motor driving force required in the rehabilitation process is calculated to achieve the purpose of rationalizing the rehabilitation movement of the patient’s lower limb. To reconstruct the patient’s motor functions, an active training control strategy based on the sandy soil model is proposed. Finally, the experimental platform of the proposed robot is constructed, and the preliminary physical experiment proves the feasibility of the lower limb rehabilitation component. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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Article
Gear Teeth Deflection Model for Spur Gears: Proposal of a 3D Nonlinear and Non-Hertzian Approach
Machines 2021, 9(10), 223; https://doi.org/10.3390/machines9100223 - 30 Sep 2021
Viewed by 382
Abstract
In this paper, a three-dimensional model for the estimation of the deflections, load sharing attributes, and contact conditions will be presented for pairs of meshing teeth in a spur gear transmission. A nonlinear iterative approach based on a semi-analytical formulation for the deformation [...] Read more.
In this paper, a three-dimensional model for the estimation of the deflections, load sharing attributes, and contact conditions will be presented for pairs of meshing teeth in a spur gear transmission. A nonlinear iterative approach based on a semi-analytical formulation for the deformation of the teeth under load will be employed to accurately determine the point of application of the load, its intensity, and the number of contacting pairs without a priori assumptions. At the end of this iterative cycle the obtained deflected shapes are then employed to compute the pressure distributions through a contact mechanics model with non-Hertzian features and a technique capable of obtaining correct results even at the free edges of the finite length contacting bodies. This approach is then applied to a test case with excellent agreement with its finite element counterpart. Finally, several results are shown to highlight the influence on the quasi-static behavior of spur gears of different kinds and amounts of flank and face-width profile modifications. Full article
(This article belongs to the Section Machine Design and Theory)
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Article
Vibrodiagnostics Faults Classification for the Safety Enhancement of Industrial Machinery
Machines 2021, 9(10), 222; https://doi.org/10.3390/machines9100222 - 30 Sep 2021
Viewed by 376
Abstract
The current digitization of industrial processes is leading to the development of smart machines and smart applications in the field of engineering technologies. The basis is an advanced sensor system that monitors selected characteristic values of the machine. The obtained data need to [...] Read more.
The current digitization of industrial processes is leading to the development of smart machines and smart applications in the field of engineering technologies. The basis is an advanced sensor system that monitors selected characteristic values of the machine. The obtained data need to be further analysed, correctly interpreted, and visualized by the machine operator. Thus the machine operator can gain a sixth sense for keeping the machine and the production process in a suitable condition. This has a positive effect on reducing the stress load on the operator in the production of expensive components and in monitoring the safe condition of the machine. The key element here is the use of a suitable classification model for data evaluation of the monitored machine parameters. The article deals with the comparison of the success rate of classification models from the MATLAB Classification Learner App. Classification models will compare data from the frequency and time domain, the data source is the same. Both data samples are from real measurements on the CNC vertical machining center (CNC-Computer Numerical Control). Three basic states representing machine tool damage are recognized. The data are then processed and reduced for the use of the MATLAB Classification Learner app, which creates a model for recognizing faults. The article aims to compare the success rate of classification models when the data source is a dataset in time or frequency domain and combination. Full article
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Article
PSIC-Net: Pixel-Wise Segmentation and Image-Wise Classification Network for Surface Defects
Machines 2021, 9(10), 221; https://doi.org/10.3390/machines9100221 - 29 Sep 2021
Viewed by 350
Abstract
Recent years have witnessed the widespread research of the surface defect detection technology based on machine vision, which has spawned various effective detection methods. In particular, the rise of deep learning has allowed the surface defect detection technology to develop further. However, these [...] Read more.
Recent years have witnessed the widespread research of the surface defect detection technology based on machine vision, which has spawned various effective detection methods. In particular, the rise of deep learning has allowed the surface defect detection technology to develop further. However, these methods based on deep learning still have some drawbacks. For example, the size of the sample data is not large enough to support deep learning; the location and recognition of surface defects are not accurate enough; the real-time performance of segmentation and classification is not satisfactory. In the context, this paper proposes an end-to-end convolutional neural network model: the pixel-wise segmentation and image-wise classification network (PSIC-Net). With the innovative design of a three-stage network structure, improved loss function and a two-step training mode, PSIC-Net can accurately and quickly segment and classify surface defects with a small dataset of training data. This model was evaluated with three public datasets, and compared with the most advanced defect detection methods. All the performance metrics prove the effectiveness and advancement of PSIC-Net. Full article
(This article belongs to the Section Machines Testing and Maintenance)
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Article
Optimization of Material Supply in Smart Manufacturing Environment: A Metaheuristic Approach for Matrix Production
Machines 2021, 9(10), 220; https://doi.org/10.3390/machines9100220 - 29 Sep 2021
Viewed by 395
Abstract
In the context of Industry 4.0, the matrix production developed by KUKA robotics represents a revolutionary solution for flexible manufacturing systems. Because of the adaptable and flexible manufacturing and material handling solutions, the design and control of these processes require new models and [...] Read more.
In the context of Industry 4.0, the matrix production developed by KUKA robotics represents a revolutionary solution for flexible manufacturing systems. Because of the adaptable and flexible manufacturing and material handling solutions, the design and control of these processes require new models and methods, especially from a real-time control point of view. Within the frame of this article, a new real-time optimization algorithm for in-plant material supply of smart manufacturing is proposed. After a systematic literature review, this paper describes a possible structure of the in-plant supply in matrix production environment. The mathematical model of the mentioned matrix production system is defined. The optimization problem of the described model is an integrated routing and scheduling problem, which is an NP-hard problem. The integrated routing and scheduling problem are solved with a hybrid multi-phase black hole and flower pollination-based metaheuristic algorithm. The computational results focusing on clustering and routing problems validate the model and evaluate its performance. The case studies show that matrix production is a suitable solution for smart manufacturing. Full article
(This article belongs to the Special Issue Smart Manufacturing)
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Article
On the Design of a Class of Rotary Compressors Using Bayesian Optimization
Machines 2021, 9(10), 219; https://doi.org/10.3390/machines9100219 - 29 Sep 2021
Viewed by 415
Abstract
The optimization process of compressors is usually regarded as a ‘black-box’ problem, in which the mathematical form underlying the relationship between design parameters and the design objective is impractical and costly to be obtained. To solve the ‘black-box’ problem, Bayesian optimization has been [...] Read more.
The optimization process of compressors is usually regarded as a ‘black-box’ problem, in which the mathematical form underlying the relationship between design parameters and the design objective is impractical and costly to be obtained. To solve the ‘black-box’ problem, Bayesian optimization has been proven as an accurate and efficient method. However, the application of such a method in the design of compressors is rarely discussed, particularly no work has been reported in terms of the positive displacement type compressor. Therefore, this paper aims to introduce the Bayesian optimization to the design of positive displacement compressors through the optimization process of the novel limaçon compressor. In this paper, a two-stage optimization process is presented, in which the first stage optimizes the geometric parameters as per design requirements and the second stage focuses on revealing an optimum setting of port geometries that improves machine performance. A numerical illustration is offered to prove the validity of the presented approach. Full article
(This article belongs to the Special Issue Advances in Positive Displacement Compressors)
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Article
Bayesian Optimization Design of Inlet Volute for Supercritical Carbon Dioxide Radial-Flow Turbine
Machines 2021, 9(10), 218; https://doi.org/10.3390/machines9100218 - 28 Sep 2021
Viewed by 312
Abstract
The radial-flow turbine, a key component of the supercritical CO2 (S-CO2) Brayton cycle, has a significant impact on the cycle efficiency. The inlet volute is an important flow component that introduces working fluid into the centripetal turbine. In-depth research on [...] Read more.
The radial-flow turbine, a key component of the supercritical CO2 (S-CO2) Brayton cycle, has a significant impact on the cycle efficiency. The inlet volute is an important flow component that introduces working fluid into the centripetal turbine. In-depth research on it will help improve the performance of the turbine and the entire cycle. This article aims to improve the volute flow capacity by optimizing the cross-sectional geometry of the volute, thereby improving the volute performance, both at design and non-design points. The Gaussian process surrogate model based parameter sensitivity analysis is first conducted, and then the optimization process is implemented by Bayesian optimization (BO) wherein the acquisition function is used to query optimal design. The results show that the optimized volute has better and more uniform flow characteristics at design and non-design points. It has a smoother off-design conditions performance curve. The total pressure loss coefficient at the design point of the optimized volute is reduced by 33.26%, and the flow deformation is reduced by 54.55%. Full article
(This article belongs to the Special Issue Emerging Techniques and Their Application in Turbomachinery)
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Article
Model-Free Predictive Current Control of Synchronous Reluctance Motor Drives for Pump Applications
Machines 2021, 9(10), 217; https://doi.org/10.3390/machines9100217 - 28 Sep 2021
Cited by 1 | Viewed by 372
Abstract
Climate changes and the lack of running water across vast territories require the massive use of pumping systems, often powered by solar energy sources. In this context, simple drives with high-efficiency motors can be expected to take hold. It is important to emphasise [...] Read more.
Climate changes and the lack of running water across vast territories require the massive use of pumping systems, often powered by solar energy sources. In this context, simple drives with high-efficiency motors can be expected to take hold. It is important to emphasise that simplicity does not necessarily lie in the control algorithm itself, but in the absence of complex manual calibration. These characteristics are met by synchronous reluctance motors provided that the calibration of the current loops is made autonomous. The goal of the present research was the development of a current control algorithm for reluctance synchronous motors that does not require an explicit model of the motor, and that self-calibrates in the first moments of operation without the supervision of a human expert. The results, both simulated and experimental, confirm this ability. The proposed algorithm adapts itself to different motor types, without the need for any initial calibration. The proposed technique is fully within the paradigm of smarter electrical drives, which, similarly to today’s smartphones, offer advanced performance by making any technological complexity transparent to the user. Full article
(This article belongs to the Special Issue Machines Predictive Control)
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Communication
Continuous Control of an Underground Loader Using Deep Reinforcement Learning
Machines 2021, 9(10), 216; https://doi.org/10.3390/machines9100216 - 27 Sep 2021
Cited by 1 | Viewed by 560
Abstract
The reinforcement learning control of an underground loader was investigated in a simulated environment by using a multi-agent deep neural network approach. At the start of each loading cycle, one agent selects the dig position from a depth camera image of a pile [...] Read more.
The reinforcement learning control of an underground loader was investigated in a simulated environment by using a multi-agent deep neural network approach. At the start of each loading cycle, one agent selects the dig position from a depth camera image of a pile of fragmented rock. A second agent is responsible for continuous control of the vehicle, with the goal of filling the bucket at the selected loading point while avoiding collisions, getting stuck, or losing ground traction. This relies on motion and force sensors, as well as on a camera and lidar. Using a soft actor–critic algorithm, the agents learn policies for efficient bucket filling over many subsequent loading cycles, with a clear ability to adapt to the changing environment. The best results—on average, 75% of the max capacity—were obtained when including a penalty for energy usage in the reward. Full article
(This article belongs to the Special Issue Design and Control of Advanced Mechatronics Systems)
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Article
A Fuzzy Drive Strategy for an Intelligent Vehicle Controller Unit Integrated with Connected Data
Machines 2021, 9(10), 215; https://doi.org/10.3390/machines9100215 - 26 Sep 2021
Viewed by 403
Abstract
In order to improve vehicle control safety in intelligent and connected environments, a fuzzy drive control strategy is proposed. Through the fusion of vehicle driving data, an early warning level model was established, and the fuzzy control method was used to obtain the [...] Read more.
In order to improve vehicle control safety in intelligent and connected environments, a fuzzy drive control strategy is proposed. Through the fusion of vehicle driving data, an early warning level model was established, and the fuzzy control method was used to obtain the appropriate torque command under the vehicle condition; torque optimization processing was performed according to the different corresponding vehicle following characteristics. The control strategy was tested and verified on an established platform. Based on the experimental results, compared with the traditional drive strategy in one-way front and rear following scenarios, the vehicle avoided excessive opening and closing of the accelerator pedal when the distance between vehicles was close, maintained the correct distance in the following situation, and had better dynamic response when the distance between vehicles was large, indicating that the proposed drive strategy had a better real-time and security performance. Full article
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